ID-Based Traitor Tracing with Relaxed Black-Box Setting for Group-Based Applications
Yi‐Fan Tseng, Raylin Tso, Shi-Sheng Sun, Ziyuan Liu, You-Qian Chen · 2024
The rise of streaming platforms has underscored the importance of traitor tracing technology in safeguarding digital content from unauthorized distribution. Traitor tracing serves as a crucial tool for enhancing content piracy by tracing the sources of leaked or illicitly distributed content. This paper focuses on the issue of ID-based traitor tracing, utilizing a relaxed black-box approach to achieve trace efficiency similar to white-box tracing, while maintaining the feasibility of black-box setting in practice. Two schemes are proposed in this work, each proven secure under the DBDH assumption. Additionally, the proposed schemes also support group-based services. Compared to existing related works, our schemes offer efficient tracing and support for group-based services and applications in the streaming platform era, highlighting the importance of traitor tracing.